Skip Nav Destination
Close Modal
Update search
Filter
- Title
- Author
- Author Affiliations
- Full Text
- Abstract
- Keyword
- DOI
- ISBN
- EISBN
- ISSN
- EISSN
- Issue
- Volume
- References
- Paper Number
Filter
- Title
- Author
- Author Affiliations
- Full Text
- Abstract
- Keyword
- DOI
- ISBN
- EISBN
- ISSN
- EISSN
- Issue
- Volume
- References
- Paper Number
Filter
- Title
- Author
- Author Affiliations
- Full Text
- Abstract
- Keyword
- DOI
- ISBN
- EISBN
- ISSN
- EISSN
- Issue
- Volume
- References
- Paper Number
Filter
- Title
- Author
- Author Affiliations
- Full Text
- Abstract
- Keyword
- DOI
- ISBN
- EISBN
- ISSN
- EISSN
- Issue
- Volume
- References
- Paper Number
Filter
- Title
- Author
- Author Affiliations
- Full Text
- Abstract
- Keyword
- DOI
- ISBN
- EISBN
- ISSN
- EISSN
- Issue
- Volume
- References
- Paper Number
Filter
- Title
- Author
- Author Affiliations
- Full Text
- Abstract
- Keyword
- DOI
- ISBN
- EISBN
- ISSN
- EISSN
- Issue
- Volume
- References
- Paper Number
NARROW
Format
Subjects
Date
Availability
1-1 of 1
Keywords: defect
Close
Follow your search
Access your saved searches in your account
Would you like to receive an alert when new items match your search?
Sort by
Proceedings Papers
Publisher: American Rock Mechanics Association
Paper presented at the 2nd International Discrete Fracture Network Engineering Conference, June 20–22, 2018
Paper Number: ARMA-DFNE-18-0685
... fracturing of the intact material. The µDFNs were generated separately from the GBMs in SR2 to create pre-existing “defects”. These geometries were created stochastically with fracture orientation, mean length and areal intensity (P21) serving as input parameters for the generation process. Following the...
Abstract
ABSTRACT: Micro discrete fracture networks (µDFN) have been embedded into Grain Boundary Models (GBM) within UDEC to simulate laboratory tests on a series of progressively larger in size numerical specimens. The initial GBMs simulating the intact rock consist of Voronoi blocks to capture the fracturing of the intact material. The µDFNs were generated separately from the GBMs in SR2 to create pre-existing “defects”. These geometries were created stochastically with fracture orientation, mean length and areal intensity (P21) serving as input parameters for the generation process. Following the generation of the µDFN geometries, the fracture networks were incorporated into the GBMs to create synthetic rock mass (SRM) models. This type of model is able to capture the behaviour of “flawed” rock samples as the defects are explicitly modelled. A sensitivity analysis is undertaken to examine the effect of micro-defect intensity on the UCS and modulus of deformation under an assumption of a constant crack length. Preliminary results highlight the impact of pre-existing defects and their geometrical configuration on the rock block strength.